1.云南省水利水电科学研究院, 云南 昆明 650228
2.云南省水土流失防治与绿色发展重点实验室, 云南 昆明 650228
刘丽(1982—),女(蒙古族),内蒙古自治区通辽市人,本科,高级工程师,主要从事区域生态安全和水土保持研究。Email:ll202499@163.com。
李加顺(1983—),男(汉族),云南省曲靖市人,硕士,高级工程师,主要从事区域生态安全和水土保持研究。Email:ljs202424@163.com。
收稿:2025-03-13,
修回:2025-07-05,
纸质出版:2025-10-10
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刘丽, 李加顺.城市化影响下云南省昆明市生态安全格局时空演变[J].水土保持通报,2025,45(5):360-371.
Liu Li, Li Jiashun. Spatiotemporal evolution of ecological security pattern under influence of urbanization in Kunming City, Yunnan Province [J]. Bulletin of Soil and Water Conservation,2025,45(5):360-371.
刘丽, 李加顺.城市化影响下云南省昆明市生态安全格局时空演变[J].水土保持通报,2025,45(5):360-371. DOI: 10.13961/j.cnki.stbctb.2025.05.040. CSTR: 32312.14.stbctb. 2025.05.040..
Liu Li, Li Jiashun. Spatiotemporal evolution of ecological security pattern under influence of urbanization in Kunming City, Yunnan Province [J]. Bulletin of Soil and Water Conservation,2025,45(5):360-371. DOI: 10.13961/j.cnki.stbctb.2025.05.040. CSTR: 32312.14.stbctb. 2025.05.040..
目的
2
对城市化影响下的城市生态安全格局时空演变开展研究,分析人类活动对生态连通性的影响,进而提出改善生态网络的策略,为城市生态保护与可持续空间治理提供理论支持与决策参考。
方法
2
以昆明市为例,采用遥感生态指数(RSEI)评估区域生境质量,并结合机器学习模型XGBoost和SHAP解释性分析工具,明确影响RSEI空间格局的主要驱动因素。基于这些驱动因素,构建生态阻力面,并利用形态学空间格局分析(MSPA)、景观连通性指数(LCI)和电路理论,构建“点-线-面”结合的生态安全格局。
结果
2
2000—2023年昆明市的生态安全格局发生了显著变化。尽管生态源面积增加了1 258.50 km
2
,生态源的总面积扩展,但生态廊道的数量减少了23条,总长度减少了201.58 km。此外,生态夹点数量减少了14个,而生态障碍点则增加了4个,这些变化严重影响了生态网络的连通性和物种的自由迁徙能力。滇池周边区域受城市扩展和人类活动影响尤为显著,成为生态阻力值最高的区域,面临较大的连通性破坏风险。
结论
2
为应对城市化带来的挑战,昆明市应加强对生态源的保护,修复关键生态廊道,减少人类活动对生态网络的干扰,并在滇池周边实施更为严格的生态保护措施,缓解城市化对生态系统的负面影响。
Objective
2
The spatiotemporal evolution of urban ecological security patterns under the influence of urbanization was researched, the impacts of human activities on ecological connectivity were analyzed, and corresponding strategies to optimize the ecological network were proposed to provides theoretical support and decision-making references for urban ecological protection and sustainable spatial governance.
Methods
2
Taking Kunming City as a case study, the remote sensing ecological index (RSEI) was employed to assess regional habitat quality. By integrating the XGBoost machine learning model with SHAP interpretability analysis tools, the main driving factors influencing the spatial pattern of RSEI were identified. Based on these driving factors, an ecological resistance surface was constructed. Subsequently, through the application of morphological spatial pattern analysis (MSPA), landscape connectivity index (LCI), and circuit theory, a comprehensive ‘point-line-plane’ ecological security pattern was established.
Results
2
From 2000 to 2023, Kunming’s ecological security pattern underwent significant changes. Although the area of ecological sources increased by 1 258.50 km
2
, representing an expansion of the total ecological source area, the number of ecological corridors decreased by 23, with a total length reduced by 201.58 km. Furthermore, the number of ecological pinch points decreased by 14, while ecological barrier points increased by 4. These alterations seriously affected the connectivity of the ecological network and the free migration capacity of species. Due to urban expansion and intensified human activities, the Dianchi Lake periphery emerged as the most severely impacted zone, exhibiting the highest ecological resistance values and facing a high risk of connectivity degradation.
Conclusion
2
To counter urbanization challenges, Kunming should strengthen ecological source protection, rehabilitate key ecological corridors, reduce human interference with the ecological network, and implement stricter ecological protection measures in the Dianchi Lake periphery to mitigate the negative impacts of urbanization on the ecosystem.
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